The non-dominated sorting genetic algorithm II (NSGA-II) is the most intensively used multi-objective evolutionary (MOEA) in real-world applications. However, contrast to several simple MOEAs analyzed also via mathematical means, no such study exists for NSGA-II so far. In this work, we show that runtime analyses are feasible NSGA-II. As particular results, prove with a population size larger t...

Abstract Robot manipulators perform a point-point task under kinematic and dynamic constraints. Due to multi-degree-of-freedom coupling characteristics, it is difficult find better desired trajectory. In this paper, multi-objective trajectory planning approach based on an improved elitist non-dominated sorting genetic algorithm (INSGA-II) proposed. Trajectory function planned with new composite...

Penjadwalan operasi pasien merupakan aktifitas penting pada kegiatan operasional rumah sakit, karena menentukan waktu pasien-pasien tertangani dengan baik. Permasalahan ini dimodelkan sebagai masalah optimasi multi-obyektif yaitu meminimalkan yang digunakan saat tindakan operasi. Masalah penjadwalan dirumuskan mixed integer programming (MIP), sehingga variabel merepresentasikan jadwal kasus lay...

To quickly get the median value of any given sequence is very important in many research fields. Some popular sort algorithms are discussed in this paper. Selection sort algorithm and bubble sort algorithm are redesigned as incomplete sort algorithms to quickly give the median value of randomly given sequence. In the new algorithms, only parts of the items in sequence need to be sorted to give ...

This paper introduces a novel multi-objective evolutionary algorithm based on cat swarm optimizationalgorithm (EMCSO) and its application to solve a multi-objective knapsack problem. The multi-objective optimizers try to find the closest solutions to true Pareto front (POF) where it will be achieved by finding the less-crowded non-dominated solutions. The proposed method applies cat swarm optim...

The time–cost tradeoff problem is one of the most important and applicable problems in project scheduling area. There are many factors that force the mangers to crash the time. This factor could be early utilization, early commissioning and operation, improving the project cash flow, avoiding unfavorable weather conditions, compensating the delays, and so on. Since there is a need to allocate e...

Bingheng Wang Dept. of Computer Science Florida Institute of Technology Melbourne FL 32904 [email protected] ABSTRACT Given a list of elements, we rearrange the list with ascending or descending order. So far the existing approaches involve Bubble Sort, Insertion Sort, Selection Sort ( respectively in worst case) performing slow. Now we introduce a new algorithm Merge Sort to solve the problem ...

despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. in this paper, moeas have been used for solving multi-objective portfolio optimization problem in tehran stock market. f...

in this study the performance and emissions characteristics of a heavy-duty, direct injection, compression ignition (ci) engine which is specialized in agriculture, have been investigated experimentally. for this aim, the influence of injection timing, load, engine speed on power, brake specific fuel consumption (bsfc), peak pressure (pp), nitrogen oxides (nox), carbon dioxide (co2), carbon mon...

An evolutionary multi-objective optimization tool based on an estimation of distribution algorithm is proposed. The algorithm uses the ranking method of non-dominated sorting genetic algorithm-II and the Parzen estimator to approximate the probability density of solutions lying on the Pareto front. The proposed algorithm has been applied to different types of test case problems and results show...